CN114025264B - Route planning method for electric power communication SDH optical transmission network - Google Patents
Route planning method for electric power communication SDH optical transmission network Download PDFInfo
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Abstract
The invention relates to a route planning method for an electric power communication SDH optical transmission network, which is technically characterized by comprising the following steps: constructing a power communication SDH optical transmission network resource model; uniformly distributing services with different importance and different bandwidths into a network; extracting service request information; if the service designates the existing service path or channel protection ring and available resources exist in the service path or channel protection ring, corresponding resources are allocated to the service to generate a service path, otherwise, a reinforcement learning method is used for solving the working route; if the service is a protection service, solving a backup route by using a reinforcement learning method, generating a channel protection ring, and distributing corresponding resources for the service; and updating the network available resources, the link risk value, the node risk value and the link load value. The invention realizes reasonable planning function for SDH optical transmission network route, provides important basis for planning design and operation and maintenance management of SDH optical transmission network, and is helpful for guaranteeing safe, stable and reliable operation of electric power system.
Description
Technical Field
The invention belongs to the technical field of SDH optical transmission networks, in particular to a route planning method for an electric power communication SDH optical transmission network.
Background
The optical transmission network of the power communication SDH (Synchronous Digital Hierarchy ) is used as an important component of the provincial and provincial backbone communication network of the national power grid company, bears the power grid core services of relay protection, stable control, dispatching automation and the like, and plays an important role in ensuring the safe, stable and reliable operation of the power system. However, with the continuous promotion of energy internet construction, the SDH optical transmission network scale is continuously enlarged, the management difficulty is increasingly increased, the unprecedented pressure is brought to operation and maintenance management personnel, and the following problems to be solved urgently appear:
(1) The structure of the electric power communication SDH optical transmission network is increasingly complex, and the management difficulty is high. Because the communication construction project is constructed in batches along with the primary line of the power grid in a staged way, and the optical cable is continuously adjusted along with the primary line, the integrity of the optical transmission network frame of each level is not strong, and the stability of the core network frame is not enough in the current stage; the communication equipment in the network is repeatedly stacked and configured, and equipment manufacturers are complex in composition.
(2) The communication lines are crisscrossed vertically and horizontally and have various properties; the distribution of optical cable routing resources is unbalanced, and part of the cross-regional optical cable routes are single. The reliability and the survivability of the electric power communication SDH optical transmission network are reduced, the influence range is wide after the occurrence of faults, the removal difficulty is high, and meanwhile, great difficulty is brought to operation and maintenance management.
In order to better manage the SDH optical transport network, the traffic routes of the power communication network must be planned reasonably. At present, the power communication network service route planning method mainly has the following problems:
(1) Network risk balancing or load balancing is considered from a single perspective only, and modeling is performed without considering both simultaneously.
(2) Most of the method only constructs evaluation indexes according to constraint conditions such as business importance, node risk, link risk and the like, and the availability of resources in the network is not considered, namely, the route required by the method is ideally considered to be mapped to the real network, and the available communication resources are necessarily present.
(3) The existing research only focuses on the primary and standby double routes in the power grid management policy, and the constraint of line heavy load (namely that a single optical fiber cannot bear more than 8 relay protection services and stability control system services) is ignored.
(4) The SDH optical transmission network for electric power communication has stronger self-healing capability, but the existing researches ignore the configured protection strategy in the network and have certain limitation.
Considering that the service transmission risk and the network traffic distribution situation are two important characteristics of the electric power communication SDH optical transmission network, the bottleneck section with the partial bandwidth utilization rate exceeding 90% exists in the backbone optical transmission network, and the limiting factors such as the partial line is overloaded or is about to be overloaded exist, so that the service route planning method is difficult to be directly applied to the real network.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a route planning method for an electric power communication SDH optical transmission network, which comprehensively considers risk and load joint balancing factors, can effectively balance network risk and load flow, and can reduce blocking rate and network service risk to a certain extent.
The invention solves the technical problems in the prior art by adopting the following technical scheme:
a route planning method for an electric power communication SDH optical transmission network comprises the following steps:
step 1, constructing a power communication SDH optical transmission network resource model;
step 2, according to the risk and load joint balancing strategy, uniformly distributing the services with different importance and different bandwidths into the network;
step 3, after the service request arrives, extracting the service type, the service source/sink node, the service bandwidth, whether the service is a protection service, a service path and a channel protection ring number;
step 4, if the service designates the existing service path or channel protection ring and available resources exist in the service path or channel protection ring, corresponding resources are allocated to the service to generate a service path, otherwise, a reinforcement learning method is used for solving the working route;
step 5, if the service is a protection service, solving the backup route by using a reinforcement learning method, generating a channel protection ring, and distributing corresponding resources for the service;
and 6, updating available network resources, a link risk value, a node risk value and a link load value.
The power communication SDH optical transmission network resource model comprises a cross time slot resource model, a node resource model, a link resource model, a network and protection resource model and a service and channel resource model;
the cross time slot resource model comprises a cross resource model and a time slot resource model, wherein the cross resource model consists of a cross connection class DXC and manages high-order cross capacity and low-order cross capacity in equipment nodes; the time slot resource model consists of an SDH data frame class ClsSDHFrame and a basic multiplexing container class SDHFlexContainer, and manages optical fiber resources in time slot granularity;
the node resource model comprises a Site model, an equipment node model, an equipment board card model and a Port model, wherein the Site model consists of Site class Site, the equipment node model consists of equipment node class DeviceNode, the equipment board card model consists of equipment board card class card, and the Port model consists of Port class Port;
the link resource model comprises an optical cable model, an optical path model and an optical Fiber model, wherein the optical cable model consists of optical cable OLGs, the optical path model consists of optical path Olink, and the optical Fiber model consists of optical Fiber;
the Network and protection resource model comprises a Network model, an MSP1+1 protection model, an MS-SPRing2 protection model and a channel protection ring model, wherein the Network model consists of a Network type Network, the MSP1+1 protection model consists of an MSP1+1 protection type MSP1_1, the MS-SPRing2 protection model consists of an MS-SPRing2 protection type MSspring2, and the channel protection ring model consists of a channel protection ring type PathProtection;
the business and Channel resource model comprises a business model, a business path model and a Channel model, wherein the business model is composed of business class Service, the business path model is composed of business path class Service path, and the Channel model is composed of Channel class Channel.
Moreover, the risk and load joint balancing policy includes a risk balancing policy including a link risk value and a node risk value and a load balancing policy including a link load value.
And, the link risk value, the node risk value and the link load value are normalized according to the following formulas:
in the method, in the process of the invention,representing link risk value, node risk value and link load value, respectively,/->Respectively representing a normalized link risk value, a node risk value and a link load value; />For link->Is>And->Respectively representing the minimum value and the maximum value of the link risk value; />And->Respectively representing the minimum value and the maximum value of the node risk value; />And->Representing the minimum and maximum values of the link load values, respectively.
Moreover, the services with different importance degrees include: relay protection service, stability control system service, dispatching automation service, dispatching telephone service, wide area phasor measurement service, video conference service, administrative telephone service, lightning positioning detection system service and transformer substation video monitoring service, wherein the importance of the services is reduced in sequence.
The specific implementation method of the step 2 is as follows: abstracting equipment nodes in an electric power communication SDH optical transmission network as nodes, abstracting optical fibers connected with the equipment nodes as links, and describing the electric power communication SDH optical transmission network as a directed multi-graphG(V，E)Wherein, the method comprises the steps of, wherein,Vrepresenting a set of nodes in a network topology;Erepresenting a networkLink sets in the topology.
The power communication service type comprises a production control large area and a management information large area, the production control large area is a safety area I and a safety area II, the safety area I service comprises a relay protection service and a stability control system service, and the safety area II service comprises an electric energy metering service and a wide area phasor measuring service; the management information large area is divided into a safety area III and a safety area IV according to real-time indexes; the safety zone III comprises a monitoring system service and a video monitoring service, and the safety zone IV comprises an administrative telephone service and a video conference service.
Moreover, the reinforcement learning method adopts a Q-learning algorithm; in the reinforcement learning method, the Q-learning algorithm is updated based on the Belman equation:
in the method, in the process of the invention,sthe current state is indicated and the current state is indicated,representing the action performed, wherein->，SA set of states is represented and,Arepresenting a set of actions executable by the agent in either state,/->Is the firstk+1 updated->Value table (Tex)>Is the firstkSecondary update->Value table (Tex)>Represent the firstkThe secondary update is in the new state->Lower->Value table (Tex)>Represent the firstkThe secondary update is in the new state->Maximum achievable ∈>Value corresponding to action +.>，/>Is the learning rate; />Is awarded; />Is a discount factor;
in the reinforcement learning algorithm, willGreedy strategy for exploration and utilization of Q-learning algorithm, setting exploration rate +.>The initial value is 1:
in the method, in the process of the invention,to explore the minimum of the rate, +.>To explore the maximum value of the rate +.>Is the exponential decay rate; />Is the current number of learning times.
In addition, the reinforcement learning method takes a risk and load joint balance strategy as each jump routing weight in the routing solving process, and each jump routing weightAs an objective function of the routing algorithm, it is expressed as follows:
in the method, in the process of the invention,and->The value ranges of the equalizing factors are 0,1]And->；For link->Is defined by two end points of (a)，VRepresenting a set of nodes in a network topology;Erepresenting a set of links in a network topology, +.>Normalized values for link risk values, +.>Normalized values for node risk values, +.>Normalized value for link load value, +.>Normalized value for the link length value, +.>Representing the number of relay protection services>Indicating the number of traffic for the stability control system.
The service path comprises two channels, namely a forward working path and a reverse working path; the channel protection ring comprises four channels, namely a forward working path, a reverse working path, a forward backup path and a reverse backup path.
The invention has the advantages and positive effects that:
1. the invention establishes a cross time slot resource model based on the actual operation data of the power grid, establishes a node resource model, a link resource model, a network and protection resource model and a service and channel resource model based on the cross time slot resource model, and confirms the relation among the models and the realization method thereof.
2. The invention integrates the risk balance strategy, the load balance strategy, the link length, the power grid management strategy, the existing network protection strategy and the network resource availability, realizes the service route planning algorithm of the power communication SDH optical transmission network based on the reinforcement Learning Q-Learning algorithm, provides an important reference for planning design and operation and maintenance management of the power communication SDH optical transmission network, and is beneficial to ensuring the safe, stable and reliable operation of the power system.
Drawings
Fig. 1 is an overall structure of a power communication SDH optical transmission network resource model according to the present invention.
FIG. 2 is a diagram of the association relationship among resource classes, resource class attributes, resource class methods, and resource classes according to the present invention.
FIG. 3 is a fully associative hierarchical model of node risk value weights according to the present invention.
Fig. 4 is a flow chart of a business route planning algorithm based on reinforcement learning and considering risk and load joint balancing in the present invention.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings.
The invention provides a route planning method for an electric power communication SDH optical transmission network, which comprises the following steps:
and 1, constructing a power communication SDH optical transmission network resource model object.
In this step, the power communication SDH optical transport network resource model object is expressed as: cross and time slot resource model, node resource model, link resource model, network and protection resource model and business and channel resource model. The cross time slot resource model is used for managing cross resources and time slot resources mainly in service route planning and simulation; the node resource model and the link resource model are used as basic elements for creating a simulation network; the network model is used for reproducing various protection policies, power communication services, service paths and channels thereof configured in the real network in the simulation network, as shown in fig. 1. The following describes each resource model separately:
the cross-slot resource model comprises a cross-slot resource model and a slot resource model. As shown in fig. 2, the cross resource model consists of cross connection class DXC, and manages high-order cross capacity and low-order cross capacity in the device node; the time slot resource model consists of an SDH data frame class ClsSDHFRAme and a basic multiplexing container class SDHFlexContainer, and manages optical fiber resources at the time slot granularity. The invention refers to the basic multiplexing structure of SDH in GB/T15940-2008 standard, models the mapping, positioning and multiplexing system of ClsSDHFrame class, and adopts UML class diagram to describe the attribute-method-relation among the classes. In addition, to reduce the complexity of the model, the process of "N×AUG-1→1×AUG-N→STM-N" in the standard is simplified to "N×AUG→STM-N".
The node resource model comprises a site model, an equipment node model, an equipment board card model and a port model. As shown in fig. 2, the Site model is composed of Site class Site, the device node model is composed of device node class DeviceNode, the device board card model is composed of device board card class card, and the Port model is composed of Port class Port.
The link resource model comprises an optical cable model, an optical path model and an optical fiber model. As shown in fig. 2, wherein the optical cable model is composed of an optical cable class OLG, the optical path model is composed of an optical path class Olink, and the optical Fiber model is composed of an optical Fiber class Fiber.
The network and protection resource model is constructed based on a common protection strategy in an electric power communication SDH optical transmission network, and comprises a network model, an MSP1+1 protection (linear multiplexing section 1+1 protection) model, an MS-SPRing2 protection (two-fiber bidirectional multiplexing section shared protection ring) model and a channel protection ring model. As shown in fig. 2, where the Network model is composed of Network class, msp1+1 protection model msp1+1 protection class msp1_1, the MS-SPRing2 protection model is composed of MS-SPRing2 protection class MSSPRing2, and the channel protection ring model is composed of channel protection ring class PathProtection.
The business and channel resource model comprises a business model, a business path model and a channel model. As shown in fig. 2, where the Service model is composed of Service class Service, the Service path model is composed of Service path class ServicePath, and the Channel model is composed of Channel class Channel.
And step 2, uniformly distributing the services with different importance and different bandwidths into the network according to the risk and load joint balancing strategy.
In this step, in order to avoid excessive concentration of risk and load of the SDH optical transmission network, the influence is increased after the failure of part of equipment nodes or optical fibers, a risk and load joint balancing strategy is adopted to uniformly distribute the services with different importance and different bandwidths into the network, so as to maintain the balance of the risk and the load as much as possible.
Specifically, the device node in the electric power communication SDH optical transmission network is abstracted to be a node based on the complex network theory, and the optical fiber connected with the device node is abstracted to be a link, so that the electric power communication SDH optical transmission network can be described as a directed multi-graph from the angle of graph theoryG(V，E). Wherein,Vrepresenting a set of nodes in a network topology;Erepresenting a set of links in a network topology.
The power communication service types are divided into two types, namely a production control large area and a management information large area, wherein the production control large area can be divided into a control area (safety area I) and a non-control area (safety area II). The control area service comprises a relay protection service, a stability control system service and the like, and the non-control area service comprises an electric energy metering service, a wide area phasor measuring service and the like. The management information large area is divided into a safety area III and a safety area IV according to real-time indexes. The security area III contains monitoring system service, video monitoring service and the like, and the security area IV contains administrative telephone service, video conference service and the like. Typical power communication services and their characteristic metrics are shown in table 1:
TABLE 1 typical Power communication service and characteristic index thereof
| Reference numeralsS k | Service type | Time delay (ms) | Bandwidth (Mbps) | Importance of businessD k |
| S 1 | Relay protection service | ≤10 | 2 | 0.9661 |
| S 2 | Stability control system service | ≤30 | 2 | 0.9448 |
| S 3 | Scheduling automation traffic | ≤100 | 2 | 0.9161 |
| S 4 | Scheduling telephone traffic | ≤150 | ≤2 | 0.8550 |
| S 5 | Wide area phasor measurement service | ≤30 | ≤2 | 0.8236 |
| S 6 | Video conference service | ≤150 | ≥N*2 | 0.5490 |
| S 7 | Administrative telephone service | ≤250 | ≤2 | 0.4739 |
| S 8 | Thunder and lightning location detection system service | ≤250 | ≤2 | 0.4651 |
| S 9 | Video monitoring service for transformer substation | ≤150 | ≥N*2 | 0.3755 |
Based on the above concept of business importance, the link risk value of the link risk weight will not be consideredDefined as link->Upper bearingKProduct of sum of class traffic importance and link failure probability:
in the method, in the process of the invention,and->For link->Two of (2)End points; />Representing link->Is defined by->Calculated, wherein->For link->Availability of (3); />Representing link->Carried firstkThe sum of the importance of class services, which is defined by +.>Calculated, wherein->For link->Carried firstkClass of service quantity,/->Is the firstkImportance of class services.
Introducing edge betweenness centrality to calculate link risk value weight, and edge betweenness centralityThe calculation formula of (2) is as follows:
in the middle ofVRepresenting a set of nodes in a network topology;Erepresenting a set of links in a network topology,representing node->And node->The number of inter-shortest paths; />Representing node->And node->Inter-link->Is used for the shortest path number of the network.
For a pair ofProcessing to obtain link->Risk value weight +.>：
Using linksRisk value weight pair link risk value without consideration of link risk weightWeighting operation is carried out to obtain link risk value with weight +.>：
Node risk value is defined as nodeUpper bearingKAnd obtaining the product of the sum of the class service importance and the node failure probability by weighting by using the node risk value weight. Node risk value->The calculation formula of (2) is as follows:
in the method, in the process of the invention,weighting the node risk value; />Representing node->Is defined by->Calculated, wherein->Is a node/>Availability of (3); />Representing nodes +.>Carried firstkThe sum of the importance of class services, which is defined by +.>Calculated, wherein->For node->Carried firstkClass of service quantity,/->Is the firstkImportance of class services.
And comprehensively considering four evaluation indexes of site grade, site scale, load grade and betweenness centrality, calculating node risk value weight by adopting a hierarchical analysis method, and constructing a complete correlation hierarchical structure model. As shown in fig. 3, the top layer of the model is a target layer, and corresponds to the target quantity node risk value weight of the invention; the middle layer is a criterion layer and consists of four evaluation indexes of site grade, site scale, load grade and betweenness centrality; the bottom layer is a scheme layer and consists of all nodes in the network.
Combining the evaluation value of each node in the network with the weight of each index, and obtaining the target by adopting the weighted summation of the formula (6)By the formula (7) pair->Processing to obtain node risk value weight +.>：
In the method, in the process of the invention,weights of four evaluation indexes of site grade, site scale, load grade and medium centrality are respectively adopted; />The evaluation values of four evaluation indexes of site grade, site scale, load grade and medium centrality are respectively obtained.
Definition nodeIs->The ratio of the remaining high-order cross capacity to the high-order cross capacity is summed with the ratio of the remaining low-order cross capacity to the low-order cross capacity. Service Admission value->The calculation formula of (2) is as follows:
in the method, in the process of the invention,respectively represent node->Remaining higher order crossovers of (2)Fork capacity and remaining low-order crossover capacity; />Respectively represent node->Higher order cross-over capacity and lower order cross-over capacity of (c).
Link load valueThe calculation formula of (2) is as follows:
in the method, in the process of the invention,representing link->Is a total bandwidth of (2); />Representing link->Is a residual bandwidth resource of (1);
respectively represent node->And node->Is a traffic admission value of (a).
The risk balance strategy and the load balance strategy are respectively determined, wherein the risk balance strategy comprises two indexes of a link risk value and a node risk value. The load balancing policy includes link load values. Considering that the calculation modes of the link risk value, the node risk value and the link load value are not identical, carrying out normalization processing on the link risk value, the node risk value and the link load value to obtain the following results:
in the method, in the process of the invention,respectively representing a link risk value, a node risk value and a link load value; />And->Respectively representing the minimum value and the maximum value of the link risk value; />And->Respectively representing the minimum value and the maximum value of the node risk value; />And->Respectively representing the minimum value and the maximum value of the link load value; />The normalized values of the three are shown.
In addition, in the process of service routing, the length of the link is also one of the constraint conditions of routing decision, so the invention applies to the linkLength of->Normalization processing is carried out to obtain:
in the method, in the process of the invention,indicating link length, +.>Respectively representing the minimum value and the maximum value of the link length; />Representing its normalized value.
Further define each skip route weightAs an objective function of the routing algorithm:
in the method, in the process of the invention,the value ranges of the equalizing factors are 0,1]And->The method comprises the steps of carrying out a first treatment on the surface of the Taking the line heavy load in the power grid management policy as a constraint condition, namely that a single optical fiber cannot bear more than 8 relay protection services and stability control system services, and using +.>Indicating (I)>Respectively representing the number of relay protection services and the number of stability control system services.
And step 3, extracting the description information such as service type, service source/destination node, service bandwidth, whether the service is protection service, service path and channel protection ring number and the like after the service request arrives.
And 4, if the service designates the existing service path or channel protection ring and available resources exist in the service path or channel protection ring, corresponding resources are allocated to the service to generate a service path, otherwise, the working route is solved by using a reinforcement learning method.
And step 5, if the service is a protection service, solving the backup route by using a reinforcement learning method, generating a channel protection ring, and distributing corresponding resources for the service.
In this step, the reinforcement learning method employs a Q-learning algorithm.
In the Q-learning algorithm, the Q-learning algorithm is updated by adopting a Belman equation:
in the method, in the process of the invention,sthe current state is indicated and the current state is indicated,representing the action performed, wherein->，SA set of states is represented and,Arepresenting a set of actions executable by the agent in either state,/->Is the firstk+1 updated->Value table (Tex)>Is the firstkSecondary update->Value table (Tex)>Represent the firstkThe secondary update is in the new state->Lower->Value table (Tex)>Represent the firstkThe secondary update is in the new state->Maximum achievable ∈>Value corresponding to action +.>，/>Is the learning rate; />Is awarded; />Is a discount factor.
In the Q-learning algorithmGreedyStrategy for exploration and utilization of Q-learning algorithm, set exploration rate +.>The initial value is 1:
in the method, in the process of the invention,to explore the minimum of the rate, +.>To explore the maximum value of the rate +.>Is the exponential decay rate; />Is the current number of learning times.
And 6, updating available network resources, a link risk value, a node risk value and a link load value.
Based on the above description, the invention realizes the route planning function of the electric power communication SDH optical transmission network based on reinforcement learning and considering the business route planning algorithm of the joint balance of risk and load, and models the electric power communication SDH optical transmission network by using a Markov decision process to map the graphG(V，E)The neighbor node selected by the route next hop is considered as an action in the markov decision process. Consider the principle of minimum hop count, and route the opposite number of the weight of each hopThe bonus value obtained as a reinforcement learning one-time action and gives an additional bonus 100 when the neighbor node selected by the route next hop is the sink node.
The route planning method of the invention can be realized by computer software, wherein the input is: electric power communication SDH optical transmission network resource model object and graphG(V，E)And each simulation parameter; the output is: the service working route also comprises a service backup route for protecting the service. The specific process flow is shown in fig. 4, and comprises the following steps:
step (1): extracting network topology and setting each simulation parameter.
Step (2): waiting for a service request.
Step (3): and (4) extracting the description information such as the service type, the service source/destination node, the service bandwidth, whether the service is protection service, the service path, the channel protection ring number and the like after the service request arrives, and executing the step (4).
Step (4): if the service designates the existing service path or channel protection ring, executing the step (5); otherwise, executing the step 6).
Step (5): judging whether available resources (including cross resources and time slot resources) exist in the corresponding service path or channel protection ring, if yes, turning to the step (10); otherwise, executing the step (6).
Step (6): firstly, a Q-Learning algorithm is called to solve a service route A1 between 1 source node and a destination node, the optical fiber passing through the route is traversed, and the other optical fiber of the optical path where the route is located is extracted to form a service route A2 between the destination node and the source node. Then judging whether the service is a protection service, if so, executing the step (7); otherwise, executing the step (8).
Step (7): from the figureG(V，E)And (3) deleting the link on the service route A1, calling the Q-Learning algorithm again to solve the service route B1 which is separated from the A1 and is looped between the source node and the destination node, extracting another optical fiber of the optical path where the service route B1 is positioned to form the service route B2 between the destination node and the source node, and executing the step (9).
Step (8): and (3) forming a service working route by the service routes A1 and A2, and executing the step (10).
Step (9): judging the direction of a channel protection ring in the service description information, if the channel protection ring is a two-fiber bidirectional channel protection ring, forming a service working route by the service routes A1 and A2, and forming a service backup route by the service routes B1 and B2; if the protection ring is a two-fiber unidirectional channel protection ring, the service routes A1 and B2 form a service working route, and the service routes B1 and A2 form a service backup route. Step (10) is performed.
Step (10): judging whether available resources (including cross resources and time slot resources) exist in the service working route and the service backup route, if so, executing the step 11); otherwise, reporting the blockage, and turning to the step (2).
Step (11): for unprotected service, two channels (respectively called a forward working path and a reverse working path) are generated according to a service working route, so as to generate a service path; for protecting the service, four channels (respectively called a forward working path, a reverse working path, a forward backup path and a reverse backup path) are generated according to the service working route and the service backup route, so as to generate a channel protection ring, and the step (12) is executed.
Step (12): corresponding resources are allocated for the service, available resources (including cross resources and time slot resources) of the network are updated, and link risk values, node risk values and link load values are updated according to the formulas (4), (5) and (13), and the process goes to the step (2).
The route planning method for the electric power communication SDH optical transmission network can be realized by the following software units:
the construction unit is used for electric power communication SDH optical transmission network resource model objects and network topology;
the acquisition unit is used for acquiring the description information such as the service type, the service source/sink node, the service bandwidth and the like;
a first checking unit for checking whether the corresponding service designates an existing service path or a channel protection ring;
a second checking unit, configured to check whether available resources (including cross resources and time slot resources) exist in the corresponding service path or channel protection ring;
a third checking unit for checking whether the corresponding service is a protection service;
a fourth checking unit, configured to check whether available resources (including cross resources and time slot resources) exist in the corresponding service working route and service backup route;
the generating unit is used for generating a responsive service path or channel protection ring after solving the working route or the standby route according to the Q-learning algorithm;
and the updating output unit is used for distributing corresponding resources for the service if the generation is successful, and updating the network available resources, the link risk value, the node risk value and the link load value.
It should be emphasized that the examples described herein are illustrative rather than limiting, and therefore the invention includes, but is not limited to, the examples described in the detailed description, as other embodiments derived from the technical solutions of the invention by a person skilled in the art are equally within the scope of the invention.
Claims (6)
1. A route planning method for an electric power communication SDH optical transmission network is characterized in that: the method comprises the following steps:
step 1, constructing a power communication SDH optical transmission network resource model;
step 2, according to the risk and load joint balancing strategy, uniformly distributing the services with different importance and different bandwidths into the network;
step 3, after the service request arrives, extracting the service type, the service source/sink node, the service bandwidth, whether the service is a protection service, a service path and a channel protection ring number;
step 4, if the service designates the existing service path or channel protection ring and available resources exist in the service path or channel protection ring, corresponding resources are allocated to the service to generate a service path, otherwise, a reinforcement learning method is used for solving the working route;
step 5, if the service is a protection service, solving the backup route by using a reinforcement learning method, generating a channel protection ring, and distributing corresponding resources for the service;
step 6, updating available network resources, link risk values, node risk values and link load values;
the risk and load joint balancing strategy comprises a risk balancing strategy and a load balancing strategy, wherein the risk balancing strategy comprises a link risk value and a node risk value, and the load balancing strategy comprises a link load value;
and respectively carrying out normalization processing on the link risk value, the node risk value and the link load value according to the following formulas:
in the method, in the process of the invention,representing link risk value, node risk value and link load value, respectively,/->Respectively representing a normalized link risk value, a node risk value and a link load value; v i 、v j For the link (v) i ，v j ) Is>And->Respectively representing the minimum value and the maximum value of the link risk value; />And->Respectively representing the minimum value and the maximum value of the node risk value; />And->Respectively representing the minimum value and the maximum value of the link load value;
the reinforcement learning method adopts a Q-learning algorithm; in the reinforcement learning method, the Q-learning algorithm is updated based on the Belman equation:
Q(s，a) k+1 ＝Q(s，a) k +α[r+γmax a′ Q(s′，a′) k -Q(s，a) k ]
wherein S represents the current state, a represents the action performed, S e S, a e A, S represents the state set, A represents the action set executable by the agent in any state, Q (S, a) k+1 Q (s, a) for the k+1st updated Q value table k Q (s ', a') for the k-th updated Q value table k Q value table, max representing the kth update in the new state s a′ Q(s′，a′) k Representing the maximum Q value which can be reached by the kth update in the new state S ', wherein the corresponding action is a', and alpha is the learning rate; r is a reward; gamma is a discount factor;
in the reinforcement learning algorithm, an epsilon greedy strategy is used for the exploration and utilization of the Q-learning algorithm, and the initial value of the exploration rate epsilon is set to be 1:
ε＝ε min +(ε max -ε min )e -decay_rate×episode
wherein ε min To explore the minimum value of the rate epsilon max To explore the maximum value of the rate, the decay rate is exponential; the epicode is the current learning times;
the reinforcement learning method takes a risk and negative cut equalization strategy as each jump routing weight in the routing solving process, and each jump routing weightAs an objective function of the routing algorithm, it is expressed as follows:
wherein a, b, c and d are equalizing factors, and the values are 0,1]And a+b+c+d=1; v i 、v j For the link (v) i ，v j ) V represents a set of nodes in the network topology; e denotes the set of links in the network topology,normalized values for link risk values, +.>Normalized values for node risk values, +.>Normalized value for link load value, +.>Normalized value for the link length value, M 1 Representing the number of relay protection services, M 2 Indicating the number of traffic for the stability control system.
2. The route planning method for an SDH optical transmission network for electric power communication according to claim 1, wherein: the power communication SDH optical transmission network resource model comprises a cross and time slot resource model, a node resource model, a link resource model, a network and protection resource model, a service and channel resource model;
the cross time slot resource model comprises a cross resource model and a time slot resource model, wherein the cross resource model consists of a cross connection class DXC and manages high-order cross capacity and low-order cross capacity in equipment nodes; the time slot resource model consists of an SDH data frame class ClsSDHFrame and a basic multiplexing container class SDHFlexContainer, and manages optical fiber resources in time slot granularity;
the node resource model comprises a Site model, an equipment node model, an equipment board card model and a Port model, wherein the Site model consists of Site class Site, the equipment node model consists of equipment node class DeviceNode, the equipment board card model consists of equipment board card class card, and the Port model consists of Port class Port;
the link resource model comprises an optical cable model, an optical path model and an optical Fiber model, wherein the optical cable model consists of optical cable OLGs, the optical path model consists of optical path Olink, and the optical Fiber model consists of optical Fiber;
the Network and protection resource model comprises a Network model, an MSP1+1 protection model, an MS-SPRing2 protection model and a channel protection ring model, wherein the Network model consists of a Network type Network, the MSP1+1 protection model consists of an MSP1+1 protection type MSP1_1, the MS-SPRing2 protection model consists of an MS-SPRing2 protection type MSspring2, and the channel protection ring model consists of a channel protection ring type PathProtection;
the business and Channel resource model comprises a business model, a business path model and a Channel model, wherein the business model is composed of business class Service, the business path model is composed of business path class Service path, and the Channel model is composed of Channel class Channel.
3. The route planning method for an SDH optical transmission network for electric power communication according to claim 1, wherein: the services with different importance degrees comprise: relay protection service, stability control system service, dispatching automation service, dispatching telephone service, wide area phasor measurement service, video conference service, administrative telephone service, lightning positioning detection system service and transformer substation video monitoring service, wherein the importance of the services is reduced in sequence.
4. The route planning method for an SDH optical transmission network for electric power communication according to claim 1, wherein: the specific implementation method of the step 2 is as follows: abstracting equipment nodes in the electric power communication SDH optical transmission network as nodes, abstracting optical fibers connected with the equipment nodes as links, and describing the electric power communication SDH optical transmission network as a directed multi-graph G (V, E), wherein V represents a node set in network topology; e denotes a set of links in the network topology.
5. The route planning method for an SDH optical transmission network for electric power communication according to claim 4, wherein: the service types of the power communication comprise two types of a production control large area and a management information large area, the production control large area is a safety area I and a safety area II, the service of the safety area I comprises a relay protection service and a stability control system service, and the service of the safety area II comprises an electric energy metering service and a wide area phasor measuring service; the management information large area is divided into a safety area III and a safety area IV according to real-time indexes; the safety zone III comprises a monitoring system service and a video monitoring service, and the safety zone IV comprises an administrative telephone service and a video conference service.
6. The route planning method for an SDH optical transmission network for electric power communication according to claim 1, wherein: the service path comprises two channels, namely a forward working path and a reverse working path; the channel protection ring comprises four channels, namely a forward working path, a reverse working path, a forward backup path and a reverse backup path.
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| CN115118649B (en) * | 2022-06-29 | 2023-07-11 | 国网山东省电力公司威海供电公司 | Automatic planning method for relay protection route of power communication network |
| CN115086187B (en) * | 2022-08-01 | 2023-09-05 | 广东电网有限责任公司 | Electric power communication channel planning method, device and storage medium based on reinforcement learning |
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